Comments for Daniel Oehm | Gradient Descendinghttp://gradientdescending.com
Data Science blogWed, 23 Jan 2019 19:12:46 +1100hourly1https://wordpress.org/?v=5.0.3Comment on Generating Synthetic Data Sets with ‘synthpop’ in R by Daniel Oehmhttp://gradientdescending.com/generating-synthetic-data-sets-with-synthpop-in-r/#comment-74
Wed, 23 Jan 2019 19:12:46 +0000http://gradientdescending.com/?p=894#comment-74The dataset SD2011 is contained in the package. Just need to load the library.
]]>Comment on Generating Synthetic Data Sets with ‘synthpop’ in R by Placid Ugoagwuhttp://gradientdescending.com/generating-synthetic-data-sets-with-synthpop-in-r/#comment-72
Tue, 22 Jan 2019 14:08:33 +0000http://gradientdescending.com/?p=894#comment-72Thanks for this wonderful analogy of data de-indentification.
Please can I have a link to the datasets?
Thank you.
]]>Comment on Unsupervised Random Forest Example by Daniel Oehmhttp://gradientdescending.com/unsupervised-random-forest-example/#comment-48
Tue, 18 Dec 2018 23:22:04 +0000http://gradientdescending.com/?p=428#comment-48Since the values of the proximity matrix are bound between [0, 1] there’s no need to. You should end up with the same result either way.
]]>Comment on Unsupervised Random Forest Example by Stevehttp://gradientdescending.com/unsupervised-random-forest-example/#comment-47
Tue, 18 Dec 2018 15:55:41 +0000http://gradientdescending.com/?p=428#comment-47Hey,
thanks for the tutorial – just a short question:
Doesn’t one have to first subtract 1 – proximity matrix to obtain a distance/dissimilarity matrix and then apply PAM on it?
]]>Comment on Advanced Survey Design and Application to Big Data by Daniel Oehmhttp://gradientdescending.com/advanced-survey-design-and-application-to-big-data/#comment-39
Mon, 03 Dec 2018 10:16:54 +0000http://gradientdescending.com/?p=460#comment-39They key is to factor in the survey weights and the stratification/clusters where possible. The survey package includes functions like svyglm() which can be used for imputing missing values taking the design object as one of the inputs. I’d also check out the mice package, it’s excellent for performing multiple imputation.
]]>Comment on Advanced Survey Design and Application to Big Data by Constantinhttp://gradientdescending.com/advanced-survey-design-and-application-to-big-data/#comment-36
Sun, 02 Dec 2018 02:37:15 +0000http://gradientdescending.com/?p=460#comment-36How do you make multiple imputation of missing data in complex survey design? I know how to combine multiple imputed datasets, but I don’t know how you create those datasets.
]]>Comment on Design Matrix for Regression Explained by Lavinia Pasvizacahttp://gradientdescending.com/design-matrix-for-regression-explained/#comment-7
Sat, 01 Sep 2018 08:20:58 +0000http://gradientdescending.com/?p=402#comment-7With thanks! Valuable information!
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